基于地理标记照片的粤港澳大湾区入境旅游流转移规律及空间结构特征  

Exploring the spatial structure and characteristics of inboundtourist flow in Guangdong-Hong Kong-Macao Greater Bay Areabased on geotagged photos

作　　者：叶晓旋 曲鸣亚 保继刚[2,3] YE Xiaoxuan;QU Mingya;BAO Jigang(Baiyun Branch of Guangzhou Urban Planning&Design Survey Research Institute,Guangzhou 510060,China;Centre for Tourism Planning&Research,Sun Yat-sen University,Guangzhou 510275,China;School of Tourism Management,SunYat-sen University,Zhuhai 528406,China)

机构地区：[1]广州市城市规划勘测设计研究院白云分院,广州510060 [2]中山大学旅游发展与规划研究中心,广州510275 [3]中山大学旅游学院,珠海528406

出　　处：《地理研究》2023年第8期2152-2171,共20页Geographical Research

摘　　要：本文基于数据挖掘技术获取了Flickr平台上2009—2019年粤港澳大湾区范围内的地理标记照片数据,综合运用自适应参数的密度聚类法、关联规则挖掘算法、社会网络分析等方法,识别出各城市内部的旅游热点区域,对入境旅游流网络的动态结构特征进行总结。研究发现:①各城市内部的旅游热点区域(AOI)可分为旅游功能类、特定功能类和复合功能类,粤港澳大湾区中存在明显的经济、城市功能驱动的旅游流。②入境旅游流在城市内和城际间的转移方向均呈现出趋向高级别-高功能的“趋高性”流势,在城市内部主要以复合功能类AOI为中心进行转移,拥有复合功能类AOI的城市在区域内部的旅游竞争力相对较强、旅游节点地位相对较高。粤港澳大湾区城际间强对流主要发生在高级别城市之间,呈现出“内密外疏,东重西轻”的多层级格局。③入境旅游流网络结构呈现出“多中心共存,广泛联结”的均衡化演进特征,2009—2019年间的网络密度不断加强,联系广度不断拓展,形成了以香港地区为主核心,深圳、广州、澳门地区为次核心,东莞、珠海、佛山为重要节点,其他城市为一般节点的多中心网络结构。本研究兼具区域和城市内部两个视角,基于“点-流-网络”的尺度嵌套框架,丰富了区域入境旅游流的研究视角与研究内容,实践上可为促进区域入境旅游发展提供科学支撑。With the aid of data mining techniques,this paper acquires geotagged photo data from 2009 to 2019 on the Flickr platform within the Guangdong-Hong Kong-Macao Greater Bay Area,and uses a combination of adaptive parameter density clustering method,association rule mining algorithm,social network analysis and other methods to identify area of interest(AOI),or tourist hot spots in different cities,as well as their supply system,accordingly.Based on the urban tourism supply analysis framework,this work explains the spatial structure and characteristics of tourist flow.As the research result manifests,(1)the functions of AOI within each city can be divided into tourism function,specific function and compound function,there are clear economic-driven and urban function-driven tourism flows in the study area.(2)The transfers of inbound tourism flows in both intracity and the intercity scales have shown a trend toward high-level and multi-functionality.At the intracity scale,tourism flows are mainly shifted around the compound-function AOI,and at the intercity scale,cities with compoundfunction AOI have relatively strong inbound tourism competitiveness and higher tourism node status,and strong mobility occurs mainly between high-level cities.The inbound tourism flow of the Greater Bay Area presents a multi-level pattern of“dense inside and sparse outside,heavy convection in the east and light in the west”.(3)The network of inbound tourist flows in this area presents a balanced evolution characteristic of"multi-center coexistence and extensive connection".From 2009 to 2019,with increasing density as well as expanding connections of inbound tourism flow network,the multi-center characteristics continued to exist,and the independence of certain nodes continued to increase,leading to a multi-center system with Hong Kong as the main core and Shenzhen,Guangzhou,and Macao as secondary cores,Dongguan,Zhuhai,and Foshan as important nodes,and other cities as general nodes.Based on the"area-flow-network"framework,this paper has b

关 键 词：地理标记照片 入境旅游 旅游热点区域 空间特征 粤港澳大湾区 

分 类 号：F592.7[经济管理—旅游管理]